How do I determine values for the thresholds and rates?
A: For now,
you will have to find working parameters manually. Note though, that
there are many possible parameters to make a network behave like in
reality. Usually a set of different parameter can change the magnitude
of some expression profiles, while their overal shape can stay the same.
So it is usually still feasible to find a set of appropriate threshold
and rate values.
If it just doesn't seem possible to find working values, then perhaps
you should start hypothesizing if something should be changed in the
supposed network structure. How long you have to seek for parameters
before you can start doubting on your network is of course difficult to
tell. But when your network has a large number of components,
automatized searching can be helpful.
That's why we are currently working on parameter
estimation for SIM-plex, against (roughly) known target profiles.
We are currently working on this feature and plan to make it available in a
mRNA levels are not equal to protein levels. What about
A: You can
define two different components: one for the mRNA and one for the protein
associated with the gene. You should do that when transcription and
translation show a clear difference in behaviour.
But with the current status of research, for many genes there is often
only mRNA level knowledge available (microarrays), or only protein
knowledge (Western Blot), and people have to work with the assumption
that mRNA upregulation will correspond with protein level rise, though a
Therefore SIM-plex makes it possible to define transcriptional
creation and transcriptional blocks, as well as chemical creation and
chemical break-down; and these four actions can be combined together for
each geneproduct. See the "Note about creation, block and break-down" in
the tutorial or in the syntax-part of the manual.
How can I model metabolic reactions?
A: This is
not what SIM-plex is made for. SIM-plex is made
for modeling regulatory interactions. SIM-plex's underlying mathematic model is
(for now) only based on stepwise activations, because this type of
mathematics makes it possible to translate if-then statements so transparently
into differential equations.
(The non-regulatory if-then-transform statements
are in fact already an extension that is quantitatively less correct in
the used mathematical framework. But it is still a very usable
extension when you model in the context of (switch-like) genetic
regulatory networks in which temporary disactivations of proteins by
phosphorylation etc. are
crucial, intermediary steps in the network.)
Also note that for more gradual binding and activation, you could define an activation
with two or three steps, based on two or three consecutive thresholds
for the activating component.
Can I have more options to decorate the plots?
can export the results to a (tab-delimited) textfile readable by Excel.
So while the plot windows show results quickly, creating fancy graphs
can happen with a specialized program, outside the simulator.